Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer.

BACKGROUND AND PURPOSE: We aimed to develop a radiomics model for the prediction of survival and chemotherapeutic benefits using pretreatment multiparameter MR images and clinicopathological features in patients with locally advanced rectal cancer (LARC). MATERIALS AND METHODS: 186 consecutive patients with LARC underwent feature extraction from the whole tumor on T2-weighted, contrast enhanced T1-weighted, and ADC images. Feature selection was based on feature stability and the Boruta algorithm. Radiomics signatures for predicting DFS (disease-free survival) were then generated using the selected features. Combining clinical risk factors, a radiomics nomogram was constructed using Cox proportional hazards regression model. The predictive performance was evaluated by Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis. RESULTS: Four features were selected to construct the radiomics signature, significantly associated with DFS (P < 0.001). The radiomics nomogram, incorporating radiomics signature and two clinicopathological variables (pN and tumor differentiation), exhibited better prediction performance for DFS than the clinicopathological model, with C-index of 0.780 (95%CI, 0.718-0.843) and 0.803 (95%CI, 0.717-0.889) in the training and validation cohorts, respectively. The radiomics nomogram-defined high-risk group had a shorter DFS, DMFS, and OS than those in the low-risk group (all P < 0.05). Further analysis showed that patients with higher nomogram-defined score exhibited a favorable response to adjuvant chemotherapy (AC) while the low-risk could not. CONCLUSION: This study demonstrated that the newly developed pretreatment multiparameter MRI-based radiomics model could serve as a powerful predictor of prognosis, and may act as a potential indicator for guiding AC in patients with LARC.

Radiomics Analysis of Multiparametric MRI for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer.

Objective: To develop and validate a radiomics predictive model based on multiparameter MR imaging features and clinical features to predict lymph node metastasis (LNM) in patients with cervical cancer. Material and Methods: A total of 168 consecutive patients with cervical cancer from two centers were enrolled in our retrospective study. A total of 3,930 imaging features were extracted from T2-weighted (T2W), ADC, and contrast-enhanced T1-weighted (cT1W) images for each patient. Four-step procedures, mainly minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) regression, were applied for feature selection and radiomics signature building in the training set from center I (n = 115). Combining clinical risk factors, a radiomics nomogram was then constructed. The models were then validated in the external validation set comprising 53 patients from center II. The predictive performance was determined by its calibration, discrimination, and clinical usefulness. Results: The radiomics signature derived from the combination of T2W, ADC, and cT1W images, composed of six LN-status-related features, was significantly associated with LNM and showed better predictive performance than signatures derived from either of them alone in both sets. Encouragingly, the radiomics signature also showed good discrimination in the MRI-reported LN-negative subgroup, with AUC of 0.825 (95% CI: 0.732-0.919). The radiomics nomogram that incorporated radiomics signature and MRI-reported LN status also showed good calibration and discrimination in both sets, with AUCs of 0.865 (95% CI: 0.794-0.936) and 0.861 (95% CI: 0.733-0.990), respectively. Decision curve analysis confirmed its clinical usefulness. Conclusion: The proposed MRI-based radiomics nomogram has good performance for predicting LN metastasis in cervical cancer and may be useful for improving clinical decision making.

Surface Engineering of a 3D Topological Network for Ultrasensitive Piezoresistive Pressure Sensors.

Polypyrrole (PPy) is a good candidate material for piezoresistive pressure sensors owing to its excellent electrical conductivity and good biocompatibility. However, it remains challenging to fabricate PPy-based flexible piezoresistive pressure sensors with high sensitivity because of the intrinsic rigidity and brittleness of the film composed of dense PPy particles. Here, a rational structure, that is, 3D-conductive and elastic topological film composed of coaxial nanofiber networks, is reported to dramatically improve the sensitivity of flexible PPy-based sensors. The film is prepared through surface modification of electrospun polyvinylidene fluoride (PVDF) nanofibers by polydopamine (PDA), in order to homogeneously deposit PPy particles on the nanofiber networks with strong interfacial adhesion (PVDF/PDA/PPy, PPP). This unique structure has a high surface area and abundant contact sites, leading to superb sensitivity against a subtle pressure. The as-developed piezoresistive pressure sensor delivers a low limit of detection (0.9 Pa), high sensitivity (139.9 kPa-1), fast response (22 ms), good cycling stability (over 10,000 cycles), and reliability, thereby showing a promising value for applications in the fields of health monitoring and artificial intelligence.

Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer.

OBJECTIVE: To develop a T2-weighted (T2W) image-based radiomics signature for the individual prediction of KRAS mutation status in patients with rectal cancer. METHODS: Three hundred four consecutive patients from center I with pathologically diagnosed rectal adenocarcinoma (training dataset, n = 213; internal validation dataset, n = 91) were enrolled in our retrospective study. The patients from center II (n = 86) were selected as an external validation dataset. A total of 960 imaging features were extracted from high-resolution T2W images for each patient. Five steps, mainly univariate statistical tests, were applied for feature selection. Subsequently, three classification methods, i.e., logistic regression (LR), decision tree (DT), and support vector machine (SVM) algorithm, were applied to develop the radiomics signature for KRAS prediction in the training dataset. The predictive performance was evaluated by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). RESULTS: Seven radiomics features were screened as a KRAS-associated radiomics signature of rectal cancer. Our best prediction model was obtained with SVM classifiers with AUC of 0.722 (95%CI, 0.654-0.790) in the training dataset. This was validated in the internal and external validation datasets with good calibration, and the corresponding AUCs were 0.682 (95% CI, 0.569-0.794) and 0.714 (95% CI, 0.602-0.827), respectively. DCA confirmed its clinical usefulness. CONCLUSIONS: The proposed T2WI-based radiomics signature has a moderate performance to predict KRAS status, and may be useful for supplementing genomic analysis to determine KRAS expression in rectal cancer patients. KEY POINTS: • T2WI-based radiomics showed a moderate diagnostic significance for KRAS status. • The best prediction model was obtained with SVM classifier. • The baseline clinical and histopathological characteristics were not associated with KRAS mutation.

A New Model and Its Application for the Dynamic Response of RGO Resistive Gas Sensor.

An reduced graphene oxide (RGO) resistive gas sensor was prepared to detect ammonia at room temperature, the result indicated that the desorption of gas (NH 3 ) molecules from a graphene-based sensor was difficult, which lead to a baseline drift. The responses of different concentrations were compared and studied. It was found that both the response rate and its acceleration were affected by the gas concentration. An Intermolecular Forces Based Model was established to explain the adsorption and desorption dynamic response curves. A new method was proposed based on this model. The first and second derivative extrema (FSDE) of the response curve can be attained quickly to calibrate the gas concentrations. The experiment results demonstrated that this new method could eliminate the baseline drift and was capable of increasing the efficiency of gas calibration significantly.

Diffusion kurtosis imaging-derived histogram metrics for prediction of KRAS mutation in rectal adenocarcinoma: Preliminary findings.

BACKGROUND: Although histological examination is the standard method for assessing genetic status, the development of a noninvasive method, which can display the heterogeneity of the whole tumor to supplement genotype analysis, might be important for personalized treatment strategies. PURPOSE: To evaluate the potential role of diffusion kurtosis imaging (DKI)-derived parameters using histogram analysis derived from whole-tumor volumes for prediction of the status of KRAS mutations in patients with rectal adenocarcinoma. STUDY TYPE: Retrospective. SUBJECTS: In all, 148 consecutive patients with histologically confirmed rectal adenocarcinoma who were treated at our institution. SEQUENCE: DKI was performed with a 3.0 T MRI system using a single-shot echo-planar imaging sequence with b values of 0, 700, 1400, and 2100 sec/mm2 . ASSESSMENT: D, K, and apparent diffusion coefficient (ADC) values were measured using whole-tumor volume histogram analysis and were compared between different KRAS mutations status. STATISTICAL TESTS: Student's t-test or Mann-Whitney U-test, and receiver operating characteristic (ROC) curves were used for statistical analysis. RESULTS: All the percentile metrics of ADC and D values were significantly lower in the mutated group than those in the wildtype group (all P < 0.05), except for the minimum value of ADC and D (both P > 0.05), while K-related percentile metrics were higher in the mutated group compared with those in the wildtype group (all P < 0.05). Regarding the comparison of the diagnostic performance of all the histogram metrics, K75th showed the highest AUC value of 0.871, and the corresponding values for sensitivity, specificity, positive predictive value, and negative predictive value were 81.43%, 78.21%, 77.03%, and 82.43%, respectively. DATA CONCLUSION: DKI metrics with whole-tumor volume histogram analysis is associated with KRAS mutations, and thus may be useful for predicting the KRAS status of rectal cancers for guiding targeted therapy. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:930-939.

Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

OBJECTIVES: To develop and validate a radiomics predictive model based on pre-treatment multiparameter magnetic resonance imaging (MRI) features and clinical features to predict a pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC) after receiving neoadjuvant chemoradiotherapy (CRT). METHODS: One hundred and eighty-six consecutive patients with LARC (training dataset, n = 131; validation dataset, n = 55) were enrolled in our retrospective study. A total of 1,188 imaging features were extracted from pre-CRT T2-weighted (T2-w), contrast-enhanced T1-weighted (cT1-w) and ADC images for each patient. Three steps including least absolute shrinkage and selection operator (LASSO) regression were performed to select key features and build a radiomics signature. Combining clinical risk factors, a radiomics nomogram was constructed. The predictive performance was evaluated by receiver operator characteristic (ROC) curve analysis, and then assessed with respect to its calibration, discrimination and clinical usefulness. RESULTS: Thirty-one of 186 patients (16.7%) achieved pCR. The radiomics signature derived from joint T2-w, ADC, and cT1-w images, comprising 12 selected features, was significantly associated with pCR status and showed better predictive performance than signatures derived from either of them alone in both datasets. The radiomics nomogram, incorporating the radiomics signature and MR-reported T-stages, also showed good discrimination, with areas under the ROC curves (AUCs) of 0.948 (95% CI, 0.907-0.989) and 0.966 (95% CI, 0.924-1.000), as well as good calibration in both datasets. Decision curve analysis confirmed its clinical usefulness. CONCLUSIONS: This study demonstrated that the pre-treatment radiomics nomogram can predict pCR in patients with LARC and potentially guide treatments to select patients for a "wait-and-see" policy. KEY POINTS: • Radiomics analysis of pre-CRT multiparameter MR images could predict pCR in patients with LARC. • Proposed radiomics signature from joint T2-w, ADC and cT1-w images showed better predictive performance than individual signatures. • Most of the clinical characteristics were unable to predict pCR.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

OBJECTIVE: To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. MATERIAL AND METHODS: 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. RESULTS: Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K10th, K90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC10th, with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). Kmean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. CONCLUSION: DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. KEY POINTS: • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Temperature-programmed multicapillary gas chromatograph microcolumn for the analysis of odorous sulfur pollutants.

We report the fabrication and performance of a silicon-on-glass micro gas chromatography eight-capillary column based on microelectromechanical systems technology that is 50 cm long, 30 µm wide, and 300 µm deep. According to the theory of a gas chromatography column, an even gas flow among different capillaries play a vital role in the peak broadening. Thus, a flow splitter structure is designed by the finite element method through the comparison of the velocity distributions of the eight-capillary columns with and without splitter as well as an open tubular column. The simulation results reveal that eight-capillary column with flow splitters can receive more uniform flow velocity in different capillaries, hence decreases the peak broadening and in turn increases the separation efficiency. The separation experiment results show that the separation efficiency of about 22 000 plates/m is achieved with the chip column temperature programmed for analysis of odorous sulfur pollutants. This figure is nearly two times higher than that of the commercial capillary column coated the similar stationary phase. And the separation time of all the components in the microcolumn is less than 3.8 min, which is faster than the commercial capillary column.

Spectral CT imaging in cervical computed tomography angiography: comparison of spectral CT monochromatic imaging and conventional CT polychromatic imaging.

OBJECTIVE: To compare the image quality of spectral CT monochromatic imaging and conventional CT polychromatic imaging for analysing CTAs in patients with cervical cancer. METHODS: In this IRB approved prospective study, 60 patients who had been diagnosed with cervical cancer underwent pelvic arterial CTA between May 2013 and July 2013. They were randomly divided into two groups; one group (30 patients) received 120 kVp polychromatic imaging (conventional CT group) and the other group (30 patients) received spectral CT imaging (spectral CT group), while all patients in both the groups received injections of 1 ml/kg of contrast agent. A total of 101 sets of monochromatic images (40-140 keV) were obtained via data reconstruction in the spectral CT group, and the monochromatic images with the best contrast-to-noise ratio (CNR) between the common iliac artery and pelvic fat (i.e. the best monochromatic energy) were selected. The best monochromatic images for the spectral CT group and the polychromatic images for the conventional CT group were postprocessed and visualised in MIP, VR and CPR mode. The CT attenuation value, noise and CNR of bilateral common iliac arteries were measured with the best monochromatic energy, as well as with 70 keV, in the spectral CT group and in the conventional CT group. The quality of the CT images was evaluated with a 5-point scale. The CTDIvol and the dose-length product (DLP) of the two groups were measured, and the results were statistically analysed. RESULTS: When images were at 50±1 keV, the common iliac artery and pelvic fat had the highest CNR, which was 72.00% higher than the images at 70 keV (P=.001) in the spectral group, and thus, the images at 50±1 keV were considered to have the best monochromatic energy. The average CT value of the internal iliac artery, which had the best monochromatic energy from the spectral CT group, was higher than that of the images from the conventional CT group (603.96±62.68 vs 251.24±28.77; P<.001), and the differences in the CNR (73.97±11.83 vs 45.21±16.63) and the subjective score (3.10±1.73 vs 2.80±1.63) were statistically significant (both P<.05). There were no significant differences in the CTDIvol (10.48±2.86 vs 12.38±1.88 mGy) or the DLP (317.76±95.50 vs 332.25±21.25 mGy cm) between the spectral and the conventional CT groups. CONCLUSION: Monochromatic spectral CT imaging has excellent soft tissue contrast and good spatial resolution and can visualise the arteries and branches supplying the tumours more clearly in patients with cervical cancer. Compared with polychromatic images, monochromatic spectral CT images are higher quality, which helps the treatment of patients with cervical cancer.

ZnO Nanoparticles/Reduced Graphene Oxide Bilayer Thin Films for Improved NH3-Sensing Performances at Room Temperature.

ZnO nanoparticles and graphene oxide (GO) thin film were deposited on gold interdigital electrodes (IDEs) in sequence via simple spraying process, which was further restored to ZnO/reduced graphene oxide (rGO) bilayer thin film by the thermal reduction treatment and employed for ammonia (NH3) detection at room temperature. rGO was identified by UV-vis absorption spectra and X-ray photoelectron spectroscope (XPS) analyses, and the adhesion between ZnO nanoparticles and rGO nanosheets might also be formed. The NH3-sensing performances of pure rGO film and ZnO/rGO bilayer films with different sprayed GO amounts were compared. The results showed that ZnO/rGO film sensors exhibited enhanced response properties, and the optimal GO amount of 1.5 ml was achieved. Furthermore, the optimal ZnO/rGO film sensor showed an excellent reversibility and fast response/recovery rate within the detection range of 10-50 ppm. Meanwhile, the sensor also displayed good repeatability and selectivity to NH3. However, the interference of water molecules on the prepared sensor is non-ignorable; some techniques should be researched to eliminate the effect of moisture in the further work. The remarkably enhanced NH3-sensing characteristics were speculated to be attributed to both the supporting role of ZnO nanoparticles film and accumulation heterojunction at the interface between ZnO and rGO. Thus, the proposed ZnO/rGO bilayer thin film sensor might give a promise for high-performance NH3-sensing applications.

The initial experience of the upper abdominal CT angiography using low-concentration contrast medium on dual energy spectral CT.

OBJECTIVE: To investigate the feasibility of using Spectral CT imaging with low contrast medium in abdominal CT angiography (CTA). SUBJECTS AND METHODS: 70 consecutive patients (40 men, 42.6 ± 20.4 years; 30 women, 46.7 ± 18.8 years) with suspected abdominal focal lesions were referred to CTA exam. They were randomly assigned into two groups. Group A: 35 patients underwent conventional CT scan of Tube voltage 120 kVp, automatic current modulation with a Noise Index of 12, ASIR 30%, and injected with Iohexol (350 mgI/ml). Group B: 35 patients underwent Spectral CT Imaging, with Tube current of 600 mA, injected with Iodixanol (270 mgI/ml). The optimal mono-energy keV was achieved using the optimal contrast noise ratio in abdominal aorta at the renal artery level relative to the erector spine muscle. Both groups were injected with an injection rate of 3.5 ml/s, and a contrast volume of 1.5 ml/kg body weight. The Hounsfield units (HU) and noise of the bilateral renal arteries and muscle of both groups, as well as the optimal monochromatic image set of Group B were measured. Two radiologists assessed all images with a 5-points scale. CTDIvol and DLP were recorded. Data were analyzed using student t test. RESULTS: The total iodine intake of Group B was 28% lower than that of Group A. The CNR of abdomen artery, celiac trunk, superior mesenteric artery, and renal artery in spectral group (at the best mono-energy of 53.0 keV) were higher than those in conventional CTA group (p < 0.001). The subjective image quality score of spectral CTA group was also rated higher than conventional CTA group (p < 0.001). CTDIvol, DLP, and effective dose of spectral group were all lower than conventional group, but there were no significant differences (p > 0.05). CONCLUSION: With 28% contrast medium reduction and reduced radiation dose, CT angiography using spectral imaging and lower concentration contrast agent provided better image quality than conventional CTA.

The enhanced formaldehyde-sensing properties of P3HT-ZnO hybrid thin film OTFT sensor and further insight into its stability.

A thin-film transistor (TFT) having an organic-inorganic hybrid thin film combines the advantage of TFT sensors and the enhanced sensing performance of hybrid materials. In this work, poly(3-hexylthiophene) (P3HT)-zinc oxide (ZnO) nanoparticles' hybrid thin film was fabricated by a spraying process as the active layer of TFT for the employment of a room temperature operated formaldehyde (HCHO) gas sensor. The effects of ZnO nanoparticles on morphological and compositional features, electronic and HCHO-sensing properties of P3HT-ZnO thin film were systematically investigated. The results showed that P3HT-ZnO hybrid thin film sensor exhibited considerable improvement of sensing response (more than two times) and reversibility compared to the pristine P3HT film sensor. An accumulation p-n heterojunction mechanism model was developed to understand the mechanism of enhanced sensing properties by incorporation of ZnO nanoparticles. X-ray photoelectron spectroscope (XPS) and atomic force microscopy (AFM) characterizations were used to investigate the stability of the sensor in-depth, which reveals the performance deterioration was due to the changes of element composition and the chemical state of hybrid thin film surface induced by light and oxygen. Our study demonstrated that P3HT-ZnO hybrid thin film TFT sensor is beneficial in the advancement of novel room temperature HCHO sensing technology.

High-separation efficiency micro-fabricated multi-capillary gas chromatographic columns for simulants of the nerve agents and blister agents.

To achieve both high speed and separation efficiency in the separation of a mixture of nerve and blister agent simulants, a high-aspect-ratio micro-fabricated multi-capillary column (MCC, a 50-cm-long, 450-µm-deep, and 60-µm-wide four-capillary column) was fabricated by the application of the microelectromechanical system (MEMS) techniques. Mixtures of chemical warfare agent (CWA) simulants - dimethyl methylphosphonate (DMMP), triethyl phosphate (TEP), and methyl salicylate - were used as samples. The fabricated MCC allowed for the separation of all the components of the gaseous mixture within 24 s, even when the difference in boiling point was 4°C, as in the case of TEP and methyl salicylate. Furthermore, interfering agents - dichloromethane, ethanol, and toluene - were also included in the subsequent gaseous mixture samples. The boiling point of these six components ranged from 78°C to 219°C. All six components were clearly separated within 70 s. This study is the first to report the clear separation of gas mixtures of components with close boiling points. The column efficiency was experimentally determined to be 12,810 plates/m.